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Autonomous research systems usually prove themselves on cherry-picked wins, human-framed topics, or a handful of preset tasks.

FARS runs the full loop at scale instead. Stage-specific agents handle ideation, planning, experimentation, and writing over a shared workspace that records proposals, code, logs, results, and manuscripts.

Its first public deployment produced 166 complete papers across 67 fine-grained AI/ML topics, and it kept the failures in the corpus rather than curating a highlight reel.

Why it matters.